Conventionally, an image processing apparatus deletes shading data from a picture signal of a subject generated by a sensor in order to form that picture signal into an easily recognizable, high-resolution picture.
For example, in an image verification apparatus such as a scanner, more accurate authentication is achieved by removing non-uniformities, in other words shading, within the output unique to that apparatus using a correction circuit.
It should be noted that there are actually two types of shading. Specifically, there is dark shading due to photoelectric converter noise and unevenness in the black output with respect to a reference level. Additionally, there is light shading due to unevenness in the sensitivity of the light source, the optical system and/or the photoelectric converters as well as the form and reflectivity of the subject.
In order to correct this type of shading, shading correction data is stored in the apparatus as default values or shading correction data is produced by photographing a white reference member prior to the actual shooting.
However, a drawback of this type of shading correction according to the conventional art is that it requires a memory for storing the shading correction data and circuits for performing correction calculations, which increases the scale of the circuitry and its cost.
Moreover, the conventional art cannot cope with the complexity of the shading correction unique to live subject verification systems such as objection verification and fingerprint authentication systems. For example, in correcting for uneven lighting due to the shape of the subject, its reflectivity, its positioning and ambient light conditions, such verification systems cannot even read the white reference for storing same as a default setting. Rather, it is necessary for such systems to detect differences in uniformity in lighting between the bright natural light of the outdoors in daylight and light sources at night or indoors, and to adapt to such changes in ambient light levels appropriately.
However, without shading correction, the tone of the darker areas within a non-uniform brightness within a picture becomes inadequate and image accuracy deteriorates. On the other hand, increasing the brightness of the light source or the output gain of the sensor in order to obtain the tone of the darker areas saturates the brightest areas of the picture, again producing inadequate tone and a consequent loss of image accuracy.